| 玉米茎秆纤维组分近红外反射光谱模型的建立 |
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| 引用本文： | 刘世伟,许莹莹,朱凯丽,宋希云,裴玉贺.玉米茎秆纤维组分近红外反射光谱模型的建立[J].玉米科学,2020,28(4):109-116. |
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| 作者姓名： | 刘世伟 许莹莹 朱凯丽 宋希云 裴玉贺 |
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| 作者单位： | 青岛农业大学生命科学学院, 山东 青岛 266109;青岛市主要农作物种质创新与应用重点实验室, 山东 青岛 266109;青岛农业大学农学院, 山东 青岛 266109;青岛市主要农作物种质创新与应用重点实验室, 山东 青岛 266109 |
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| 基金项目： | 山东省现代农业产业技术体系玉米产业创新团队项目（SDAIT-02-01）、山东省农业良种工程项目（2017LZGC005） |
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| 摘 要： | 以200份玉米自交系作为试验材料,利用近红外反射光谱技术建立3种茎秆组分的近红外光谱模型,研究更快速、准确地测定玉米茎秆中木质素、纤维素和半纤维素的含量的方法。结果表明,在4 017.94～8 053.28、4 017.94～8 067.89和4 027.08～8 928.20谱区内建立的测定玉米茎秆木质素、纤维素和半纤维素含量的近红外光谱模型效果最好。利用偏最小二乘回归法建立校正模型,木质素、纤维素和半纤维素的校正相关系数分别为0.932 9、0.925 1和0.926 5,校正标准差分别为1.57、1.68和1.18。选取30份玉米茎秆样品作为检验集对模型进行验证,木质素、纤维素和半纤维素的外部相关系数分别为0.938 9、0.891 1和0.905 0,其预测标准差分别为1.57、2.14和1.49。同样选取30份茎秆样品对模型进行交叉验证,其相关系数分别为0.897 3、0.944 2和0.891 8,交叉验证标准差分别为1.87、2.32和1.43。研究结果表明,所建模型质量较好,能快速、准确测量玉米茎秆木质素、纤维素和半纤维素含量。
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| 关 键 词： | 玉米 木质素 纤维素 半纤维素 近红外光谱 |
| 收稿时间： | 2019/9/10 0:00:00 |
Establishment of Near-Infrared Reflectance Spectroscopy Models of Fiber Composition in Corn Stalk |
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| LIU Shi-wei,XU Ying-ying,ZHU Kai-li,PEI Yu-he,SONG Xi-yun.Establishment of Near-Infrared Reflectance Spectroscopy Models of Fiber Composition in Corn Stalk[J].Journal of Maize Sciences,2020,28(4):109-116. |
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| Authors: | LIU Shi-wei XU Ying-ying ZHU Kai-li PEI Yu-he SONG Xi-yun |
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| Institution: | College of Life Science, Qingdao Agricultural University, Qingdao 266109;Qingdao Key Lab of Germplasm Innovation and Application of Major Crops, Qingdao 266109, China;College of Agronomy, Qingdao Agricultural University, Qingdao 266109;Qingdao Key Lab of Germplasm Innovation and Application of Major Crops, Qingdao 266109, China |
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| Abstract: | In order to determine the contents of lignin, cellulose and hemicellulose more rapidly and accurately, the near-infrared reflectance spectroscopy(NIRS) models of fiber composition in corn stalk were constructed with 200 corn inbred lines as experimental materials. The results showed that the NIRS models of lignin, cellulose and hemicellulose content in corn stalk established in the spectral regions of 4 017.94-8 053.28, 4 017.94-8 067.89, and 4 027.08-8 928.20 were the best. The calibration model was established by partial least squares(PLS), and the corrected correlation coefficients of lignin, cellulose and hemicellulose were 0.932 9, 0.925 1, and 0.926 5, and the root mean square error of calibration were 1.57, 1.68, and 1.18, respectively. In order to verify the model, thirty corn stalk samples were selected as the test set. The external correlation coefficients of lignin, cellulose and hemicellulose were 0.938 9, 0.891 1, and 0.905 0, respectively, and the root mean square errors of prediction(RMSEP) were 1.57, 2.14, and 1.49, respectively. The models were also cross-validated with thirty stalk samples, and the cross-validation correlation coefficients were 0.897 3, 0.944 2, and 0.891 8, respectively, and the root mean square error of cross-validation ware 1.87, 2.32, and 1.43, respectively. The results showed that the models have good quality and can determine the contents of lignin, cellulose and hemicellulose in corn stalk quickly and accurately. |
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| Keywords: | Corn Lignin Cellulose Hemicellulose Near infrared spectroscopy |
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